Inter- and intraspecific variation in grass phytolith shape and size: a geometric morphometrics perspective
Jazyk angličtina Země Velká Británie, Anglie Médium print
Typ dokumentu časopisecké články, práce podpořená grantem
PubMed
32463863
PubMed Central
PMC7789106
DOI
10.1093/aob/mcaa102
PII: 5848299
Knihovny.cz E-zdroje
- Klíčová slova
- Brachypodium pinnatum, Brachypodium sylvaticum, Phytolith analysis, generalized Procrustes superimposition, intraspecific variation, landmark-based geometric morphometrics, paleoecology,
- MeSH
- analýza hlavních komponent MeSH
- analýza rozptylu MeSH
- diskriminační analýza MeSH
- rostliny * MeSH
- zkameněliny * MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
BACKGROUND AND AIMS: The relative contributions of inter- and intraspecific variation to phytolith shape and size have only been investigated in a limited number of studies. However, a detailed understanding of phytolith variation patterns among populations or even within a single plant specimen is of key importance for the correct taxonomic identification of grass taxa in fossil samples and for the reconstruction of vegetation and environmental conditions in the past. In this study, we used geometric morphometric analysis for the quantification of different sources of phytolith shape and size variation. METHODS: We used landmark-based geometric morphometric methods for the analysis of phytolith shapes in two extant grass species (Brachypodium pinnatum and B. sylvaticum). For each species, 1200 phytoliths were analysed from 12 leaves originating from six plants growing in three populations. Phytolith shape and size data were subjected to multivariate Procrustes analysis of variance (ANOVA), multivariate regression, principal component analysis and linear discriminant analysis. KEY RESULTS: Interspecific variation largely outweighed intraspecific variation with respect to phytolith shape. Individual phytolith shapes were classified with 83 % accuracy into their respective species. Conversely, variation in phytolith shapes within species but among populations, possibly related to environmental heterogeneity, was comparatively low. CONCLUSIONS: Our results imply that phytolith shape relatively closely corresponds to the taxonomic identity of closely related grass species. Moreover, our methodological approach, applied here in phytolith analysis for the first time, enabled the quantification and separation of variation that is not related to species discrimination. Our findings strengthen the role of grass phytoliths in the reconstruction of past vegetation dynamics.
Department of Botany Faculty of Sciences Charles University Prague Benátská Praha Czech Republic
Institute of Archaeology Czech Academy of Sciences Letenská Praha Czech Republic
Zobrazit více v PubMed
Adams DC, Otárola-Castillo E. 2013. geomorph: an R package for the collection and analysis of geometric morphometric shape data. Methods in Ecology and Evolution 4: 393–399.
Adams DC, Rohlf FJ, Slice DE. 2013. A field comes of age: geometric morphometrics in the 21st century. Hystrix, the Italian Journal of Mammalogy 24: 7–14
Albert RM, Lavi O, Estroff L, Weiner S. 1999. Mode of occupation of Tabun Cave, Mt Carmel, Israel during the Mousterian period: a study of the sediments and phytoliths. Journal of Archaeological Science 26: 1249–1260.
Alexandre A, Meunier JD, Lezine AM, Vincens A, Schwartz D. 1997. Phytoliths: indicators of grassland dynamics during the late Holocene in intertropical Africa. Palaeogeography, Palaeoclimatology, Palaeoecology 136: 213–232.
Ball TB, Brotherson JD. 1992. The effect of varying environmental conditions on phytolith morphometries in two species of grass (Bouteloua curtipendula and Panicum virgatum). Scanning Microscopy 6: 1163–1181.
Ball TB, Brotherson JD, Gardner JS. 1993. A typologic and morphometric study of variation in phytoliths from einkorn wheat (Triticum monococcum). Canadian Journal of Botany 71: 1182–1192.
Ball TB, Gardner JS, Brotherson JD. 1996. Identifying phytoliths produced by the inflorescence bracts of three species of wheat (Triticum monococcum L., T. dicoccon Schrank., and T. aestivum L.) using computer-assisted image and statistical analyses. Journal of Archaeological Science 23: 619–632.
Ball TB, Gardner JS, Anderson N. 1999. Identifying inflorescence phytoliths from selected species of wheat (Triticum monococcum, T. dicoccon, T. dicoccoides, and T. aestivum) and barley (Hordeum vulgare and H. spontaneum) (Gramineae). American Journal of Botany 86: 1615–1623. PubMed
Ball TB, Ehlers R, Standing MD. 2009. Review of typologic and morphometric analysis of phytoliths produced by wheat and barley. Breeding Science 59: 505–512.
Ball TB, Davis A, Evett RR, et al. 2016. Morphometric analysis of phytoliths: recommendations towards standardization from the International Committee for Phytolith Morphometrics. Journal of Archaeological Science 68: 106–111.
Barboni D, Bremond L. 2009. Phytoliths of East African grasses: an assessment of their environmental and taxonomic significance based on floristic data. Review of Palaeobotany and Palynology 158: 29–41.
Barboni D, Bremond L, Bonnefille R. 2007. Comparative study of modern phytolith assemblages from inter-tropical Africa. Palaeogeography, Palaeoclimatology, Palaeoecology 246: 454–470.
Barboni D, Ashley GM, Dominguez-Rodrigo M, Bunn HT, Mabulla AZP, Baquedano E. 2010. Phytoliths infer locally dense and heterogeneous paleovegetation at FLK North and surrounding localities during upper Bed I time, Olduvai Gorge, Tanzania. Quaternary Research 74: 344–354.
Bastir M, Torres-Tamayo N, Palancar CA, et al. 2019. Geometric morphometric studies in the human spine. In: Been E, Gómez-Olivencia A, Ann Kramer P, eds. Spinal evolution. Cham: Springer, 361–386.
Blinnikov MS, Busacca A, Whitlock C. 2002. Reconstruction of the Late Pleistocene grassland of the Columbia basin, Washington, USA, based on phytolith records in loess. Palaeogeography, Palaeoclimatology, Palaeoecology 177: 77–101.
Bookstein FL. 1997. Landmark methods for forms without landmarks: morphometrics of group differences in outline shape. Medical Image Analysis 1: 225–243. PubMed
Bookstein FL. 2013. Random walk as a null model for high-dimensional morphometrics of fossil series: geometrical considerations. Paleobiology 39: 52–74.
Bremond L, Alexandre A, Hély C, Guiot J. 2005. A phytolith index as a proxy of tree cover density in tropical areas: calibration with leaf area index along a forest–savanna transect in southeastern Cameroon. Global and Planetary Change 45: 277–293.
Cai Z, Ge S. 2017. Machine learning algorithms improve the power of phytolith analysis: a case study of the tribe Oryzeae (Poaceae). Journal of Systematics and Evolution 55: 377–384.
Chytrý M, Tichý L, Dřevojan P, Sádlo J, Zelený D. 2018. Ellenberg-type indicator values for the Czech flora. Preslia 90: 83–103.
Cooke J, Leishman MR. 2011. Is plant ecology more siliceous than we realise? Trends in Plant Science 16: 61–68. PubMed
Delhon C, Alexandre A, Berger JF, Thiebault S, Brochier JL, Meunier JD. 2003. Phytolith assemblages as a promising tool for reconstructing Mediterranean Holocene vegetation. Quaternary Research 59: 48–60.
Dryden IL, Mardia KV. 2016. Statistical shape analysis: with applications in R, Vol. 995 Chichester: John Wiley & Sons.
Dunn RE, Le TY, Strömberg CA. 2015. Light environment and epidermal cell morphology in grasses. International Journal of Plant Sciences 176: 832–847.
Epstein E. 2009. Silicon: its manifold roles in plants. Annals of Applied Biology 155: 155–160.
Evett RR, Bartolome JW. 2013. Phytolith evidence for the extent and nature of prehistoric Californian grasslands. The Holocene 23: 1644–1649.
Evett RR, Cuthrell RQ. 2013. Phytolith evidence for a grass-dominated prairie landscape at Quiroste Valley on the Central Coast of California. California Archaeology 5: 319–335.
Evett RR, Cuthrell RQ. 2016. A conceptual framework for a computer-assisted, morphometric-based phytolith analysis and classification system. Journal of Archaeological Science 68: 70–78.
Fahmy AG. 2008. Diversity of lobate phytoliths in grass leaves from the Sahel region, West Tropical Africa: tribe Paniceae. Plant Systematics and Evolution 270: 1–23.
Fredlund GG, Tieszen LT. 1994. Modern phytolith assemblages from the North American great plains. Journal of Biogeography 21: 321–335.
Fredlund GG, Tieszen LL. 1997. Phytolith and carbon evidence for Late Quaternary vegetation and climate change in the Southern Black Hills, South Dakota. Quaternary Research 47: 206–217.
Gallego L, Distel RA. 2004. Phytolith assemblages in grasses native to central Argentina. Annals of Botany 94: 865–874. PubMed PMC
Ge Y, Lu H, Zhang J, Wang C, He K, Huan X. 2018. Phytolith analysis for the identification of barnyard millet (Echinochloa sp.) and its implications. Archaeological and Anthropological Sciences 10: 61–73.
Gunz P, Mitteroecker P. 2013. Semilandmarks: a method for quantifying curves and surfaces. Hystrix, the Italian Journal of Mammalogy 24: 103–109.
Hammer Ø, Harper DAT, Ryan PD. 2001. PAST: paleontological statistics software package for education and data analysis. Palaeontologia Electronica 4: 9.
Hart TC. 2016. Issues and directions in phytolith analysis. Journal of Archaeological Science 68: 24–31.
Hodson MJ, White PJ, Mead A, Broadley MR. 2005. Phylogenetic variation in the silicon composition of plants. Annals of Botany 96: 1027–1046. PubMed PMC
International Committee for Phytolith Taxonomy (ICPT) 2019. International code for phytolith nomenclature (ICPN) 2.0. Annals of Botany 124: 189–199. PubMed PMC
Katz O. 2015. Silica phytoliths in angiosperms: phylogeny and early evolutionary history. New Phytologist 208: 642–646. PubMed
Katz O. 2019. Silicon content is a plant functional trait: implications in a changing world. Flora 254: 88–94.
Katz O, Lev-Yadun S, Bar P. 2013. Plasticity and variability in the patterns of phytolith formation in Asteraceae species along a large rainfall gradient in Israel. Flora 208: 438–444.
Klingenberg CP. 2015. Analyzing fluctuating asymmetry with geometric morphometrics: concepts, methods, and applications. Symmetry 7: 843–934.
Kuhl FP, Giardina CR. 1982. Elliptic Fourier features of a closed contour. Computer Graphics and Image Processing 18: 236–258.
Kumar S, Milstein Y, Brami Y, Elbaum M, Elbaum R. 2017. Mechanism of silica deposition in sorghum silica cells. New Phytologist 213: 791–798. PubMed
Liu L, Jie D, Liu H, et al. 2016. Response of phytoliths in Phragmites australis to environmental factors in northeast China. Ecological Engineering 92: 119–131.
Lu H, Liu KB. 2003. Morphological variations of lobate phytoliths from grasses in China and the south-eastern United States. Diversity and Distributions 9: 73–87.
Lu H, Zhang J, Wu N, Liu KB, Xu D, Li Q. 2009. Phytoliths analysis for the discrimination of Foxtail millet (Setaria italica) and Common millet (Panicum miliaceum). PLoS One 4: e4448. PubMed PMC
Madella M, Jones MK, Echlin P, Powers-Jones A, Moore M. 2009. Plant water availability and analytical microscopy of phytoliths: implications for ancient irrigation in arid zones. Quaternary International 193: 32–40.
McCune JL, Vellend M, Pellatt MG. 2015. Combining phytolith analysis with historical ecology to reveal the long-term, local-scale dynamics within a savannah–forest landscape mosaic. Biodiversity and Conservation 24: 609–626.
Metcalfe CR. 1960. Anatomy of the monocotyledons. I. Gramineae. Oxford: Clarendon Press.
Mitteroecker P, Bookstein F. 2011. Linear discrimination, ordination, and the visualization of selection gradients in modern morphometrics. Evolutionary Biology 38: 100–114.
Mulholland SC, Rapp G eds. 1992. A morphological classification of grass silica-bodies. In: Phytolith systematics. Boston: Springer, 65–89.
Mulholland SC, Rapp G Jr, Ollendorf AL. 1988. Variation in phytoliths from corn leaves. Canadian Journal of Botany 66: 2001–2008.
Neumann K, Fahmy A, Lespez L, Ballouche A, Huysecom E. 2009. The Early Holocene palaeoenvironment of Ounjougou (Mali): phytoliths in a multiproxy context. Palaeogeography, Palaeoclimatology, Palaeoecology 276: 87–106.
Neustupa J. 2013. Patterns of symmetric and asymmetric morphological variation in unicellular green microalgae of the genus Micrasterias (Desmidiales, Viridiplantae). Fottea 13: 53–63.
Out WA, Madella M. 2016. Morphometric distinction between bilobate phytoliths from Panicum miliaceum and Setaria italica leaves. Archaeological and Anthropological Sciences 8: 505–521.
Out WA, Madella M. 2017. Towards improved detection and identification of crop by-products: morphometric analysis of bilobate leaf phytoliths of Pennisetum glaucum and Sorghum bicolor. Quaternary International 434: 1–14.
Out WA, Pertusa Grau JF, Madella M. 2014. A new method for morphometric analysis of opal phytoliths from plants. Microscopy and Microanalysis 20: 1876–1887. PubMed
Pérez R, De Ciurana J, Riba C. 2006. The characterization and specification of functional requirements and geometric tolerances in design. Journal of Engineering Design 17: 311–324.
Piperno DR. 2006. Phytoliths: a comprehensive guide for archaeologists and paleoecologists. Lanham, New York, Toronto, Oxford: AltaMira Press (Rowman & Littlefield).
Polly PD, Motz GJ. 2016. Patterns and processes in morphospace: geometric morphometrics of three-dimensional objects. The Paleontological Society Papers 22: 71–99.
Portillo M, Ball T, Manwaring J. 2006. Morphometric analysis of inflorescence phytoliths produced by Avena sativa L. and Avena strigos schreb. Economic Botany 60: 121–129.
Portillo M, Ball TB, Wallace M, et al. 2019. Advances in morphometrics in archaeobotany. Environmental Archaeology 25: 246–256.
Prasad V, Strömberg CA, Leaché AD, et al. 2011. Late Cretaceous origin of the rice tribe provides evidence for early diversification in Poaceae. Nature Communications 2: 480. PubMed
Prychid CJ, Rudall PJ, Gregory M. 2003. Systematics and biology of silica bodies in monocotyledons. The Botanical Review 69: 377–440.
R Core Team 2018. R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing.
Renvoize SA. 1987. A survey of leaf-blade anatomy in grasses XI. Paniceae. Kew Bulletin 1987: 739–768.
Rohlf FJ. 2015. The tps series of software. Hystrix, the Italian Journal of Mammalogy 26: 9–12.
Rosen AM. 1992. Preliminary identification of silica skeletons from Near Eastern archaeological sites: an anatomical approach. In: Mulholland SC, Rapp G, eds. Phytolith systematics. Boston: Springer, 129–147.
Rovner I. 2004. On transparent blindfolds: comments on identifying maize in Neotropical sediments and soils using cob phytoliths. Journal of Archaeological Science 31: 815–819.
Rovner I, Russ JC. 1992. Darwin and design in phytolith systematics: morphometric methods for mitigating redundancy. In: Mulholland SC, Rapp G, eds. Phytolith systematics. Boston: Springer, 253–276.
Rudall PJ, Prychid CJ, Gregory T. 2014. Epidermal patterning and silica phytoliths in grasses: an evolutionary history. The Botanical Review 80: 59–71.
Savriama Y. 2018. A step-by-step guide for geometric morphometrics of floral symmetry. Frontiers in Plant Science 9: 1433. PubMed PMC
Savriama Y, Klingenberg CP. 2011. Beyond bilateral symmetry: geometric morphometric methods for any type of symmetry. BMC Evolutionary Biology 11: 280. PubMed PMC
Savriama Y, Neustupa J, Klingenberg CP. 2010. Geometric morphometrics of symmetry and allometry in Micrasterias rotata (Zygnemophyceae, Viridiplantae). Nova Hedwigia 136: 43–54.
Schoelynck J, Bal K, Backx H, Okruszko T, Meire P, Struyf E. 2010. Silica uptake in aquatic and wetland macrophytes: a strategic choice between silica, lignin and cellulose? New Phytologist 186: 385–391. PubMed
Shillito LM. 2013. Grains of truth or transparent blindfolds? A review of current debates in archaeological phytolith analysis. Vegetation History and Archaeobotany 22: 71–82.
Skinner RH, Nelson CJ. 1995. Elongation of the grass leaf and its relationship to the phyllochron. Crop Science 35: 4–10.
Solomonova MY, Blinnikov MS, Silantyeva MM, Speranskaja NY. 2019. Influence of moisture and temperature regimes on the phytolith assemblage composition of mountain ecosystems of the mid latitudes: a case study from the Altay Mountains. Frontiers in Ecology and Evolution. doi: 10.3389/fevo.2019.00002. DOI
Soreng RJ, Peterson PM, Romaschenko K, et al. 2017. A worldwide phylogenetic classification of the Poaceae (Gramineae) II: An update and a comparison of two 2015 classifications. Journal of Systematics and Evolution 55: 259–290.
Strömberg CA, Di Stilio VS, Song Z. 2016. Functions of phytoliths in vascular plants: an evolutionary perspective. Functional Ecology 30: 1286–1297.
Strömberg CA, Dunn RE, Crifò C, Harris EB. 2018. Phytoliths in paleoecology: analytical considerations, current use, and future directions. In: Croft DA, Su D, Simpson SW, eds. Methods in Paleoecology. Cham: Springer, 235–287.
Strömberg CA, Werdelin L, Friis EM, Saraç G. 2007. The spread of grass-dominated habitats in Turkey and surrounding areas during the Cenozoic: phytolith evidence. Palaeogeography, Palaeoclimatology, Palaeoecology 250: 18–49.
Tsartsidou G, Lev-Yadun S, Albert RM, Miller-Rosen A, Efstratiou N, Weiner S. 2007. The phytolith archaeological record: strengths and weaknesses evaluated based on a quantitative modern reference collection from Greece. Journal of Archaeological Science 34: 1262–1275.
Twiss PC. 1992. Predicted world distribution of C 3 and C 4 grass phytoliths. In:Mulholland SC, Rapp G, eds. Phytolith systematics. Boston: Springer, 113–128.
Twiss PC, Suess E, Smith RM. 1969. Morphological classification of grass phytoliths 1. Soil Science Society of America Journal 33: 109–115.
Whang S, Kim K, Hess W. 1998. Variation of silica bodies in leaf epidermal long cells within and among seventeen species of Oryza (Poaceae). American Journal of Botany 85: 461. PubMed
Zelditch ML, Swiderski DL, Sheets DH. 2012. Geometric morphometrics for biologists: a primer, 2nd edn. London: Academic Press.
Zhang J, Lu H, Liu M, Diao X, Shao K, Wu N. 2018. Phytolith analysis for differentiating between broomcorn millet (Panicum miliaceum) and its weed/feral type (Panicum ruderale). Scientific Reports 8: 1–9. PubMed PMC
Phylogenetic, ecological and intraindividual variability patterns in grass phytolith shape